Open AccessThe establishment and evaluation of a new model for the prediction of Children B-ALL based on TARGET
Author(s) -
Xiangyu Gao,
Li Chen
Publication year - 2020
Publication title -
medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.59
H-Index - 148
eISSN - 1536-5964
pISSN - 0025-7974
DOI - 10.1097/md.0000000000020115
Subject(s) - medicine , nomogram , receiver operating characteristic , lasso (programming language) , stage (stratigraphy) , area under the curve , incidence (geometry) , calibration , statistics , mathematics , computer science , paleontology , geometry , world wide web , biology
B lymphocytic leukemia (B-ALL) is a hematopoietic malignant disease characterized by an accumulation of early B cells. This study aimed to construct a children B-ALL Nomogram prediction model based on Therapeutically Applicable Research to Generate Effective Treatments database, so as to further guide clinical diagnose and treatment. Clinical data related to children B-ALL were collected from the TARGET database, among which, the stage II clinical data were used as the prediction model, while the stage I clinical data were utilized as the external verification model. The stage II clinical factors were analyzed through Lasso regression analysis to screen the risk factors for the construction of Nomogram prediction model. In addition, the model prediction capacity and accuracy were verified internally and externally using the ROC curve, C-index and calibration curve, respectively. A total of 1316 B-ALL children were enrolled in this study. Lasso regression analysis revealed that, Age, Gender, WBC, CNSL, MRD29, BMR, CNS R, BCR-ABL1, BMA29, DS, and DI were the important prognostic risk factors. The C-index values of internal and external verification models were 0.870 and 0.827, respectively, revealing the ideal model discriminating capacity. Besides, the calibration curve had high contact ratio, which suggested favorable consistency between the incidence predicted by the model and the actual incidence. Moreover, the AUC values of the ROC curve were 0.858, 0.787, 0.898, and 0.867, respectively, indicating high model prediction accuracy in predicting the 3- and 5-year survival rates of children with B-ALL.The Nomogram prediction model plotted in this study exhibits favorable prediction capacity and clinical practicability for the survival rate of B-ALL children, which contributes to patients screening and clinical intervention.